{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T20:45:31Z","timestamp":1777927531686,"version":"3.51.4"},"reference-count":27,"publisher":"SAGE Publications","issue":"10","license":[{"start":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T00:00:00Z","timestamp":1716508800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Yunnan Provincial Science and Technology Plan Project","award":["202302AD080006"],"award-info":[{"award-number":["202302AD080006"]}]},{"name":"Natural Science Foundation Program of Shandong Province","award":["ZR2019YQ28"],"award-info":[{"award-number":["ZR2019YQ28"]}]},{"name":"Taishan Scholar Program of Shandong Province","award":["tsqn202211240"],"award-info":[{"award-number":["tsqn202211240"]}]},{"name":"The Development Plan of Youth Innovation Team of University in Shandong Province","award":["2019KJN007"],"award-info":[{"award-number":["2019KJN007"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering"],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:p>This paper investigates the design problem of a set of distributed filters. These adaptive event-triggered (AET) filters have the [Formula: see text] property and are suitable for sensor networks characterized by random measurement data loss and dynamic topology switching. In a distributed filtering network, each local filter estimates the system\u2019s state not only relying on the node\u2019s individual information but also using information from neighboring nodes in the network topology. The adaptive event triggering condition is determined by the combination of the latest release data of the filter itself, the estimated value of the current moment, and the latest release data of the neighboring nodes. The event triggering mechanism adopts a threshold adaptive adjustment scheme, which dynamically changes the threshold parameter according to the filtering error under the premise of guaranteeing the filter performance, thus maximally saving the network communication resources. Initially, we used a binary sequence to describe the random loss of sensor measurements, and a Markov chain is used to describe the switching of the filtering network topology. Secondly, a Lyapunov function is created to examine the [Formula: see text] performance index of the filtering error system and investigate its mean square exponential stability. Subsequently, the distributed filter is formulated, and its parameters are determined using the linear matrix inequality approach. Ultimately, the validity of the proposed method is substantiated through numerical illustrations.<\/jats:p>","DOI":"10.1177\/09596518241247864","type":"journal-article","created":{"date-parts":[[2024,5,24]],"date-time":"2024-05-24T03:00:56Z","timestamp":1716519656000},"page":"1845-1856","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Distributed l2\u2212l\u221e filtering over wireless sensors based on adaptive event triggering"],"prefix":"10.1177","volume":"238","author":[{"given":"Zhongqi","family":"Li","sequence":"first","affiliation":[{"name":"School of Automation and Electrical Engineering, Linyi University, Linyi, Shandong, P. R. 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